Cumulative Neutral Loss Model for Fragment Deconvolution in Electrospray Ionization High-Resolution Mass Spectrometry Data.

ABSTRACT: Clean high-resolution mass spectra (HRMS) are essential to a successful structural elucidation of an unknown feature during nontarget analysis (NTA) workflows. This is a crucial step, particularly for the spectra generated during data-independent acquisition or during direct infusion experiments. The most commonly available tools only take advantage of the time domain for spectral cleanup. Here, we present an algorithm that combines the time domain and mass domain information to perform spectral deconvolution. The algorithm employs a probability-based cumulative neutral loss (CNL) model for fragment deconvolution. The optimized model, with a mass tolerance of 0.005 Da and a score_CNL threshold of 0.00, was able to achieve a true positive rate (TPr) of 95.0%, a false discovery rat

SUBMITTER: van Herwerden D 

PROVIDER: S-EPMC10448439 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature